
Why codex /goal fails on complex workflows: compaction amnesia and context rotHi HN,When Openai released `/goal` earlier this month, I was really excited to try it for long-horizon tasks. But after using it, it didn't blow me away and i did some digging and found a major architectural flaw when using it for complex multi-issue workflows: context rot.This isn't anything new, but given how openai positioned this feature to developers, i was let down by how they'd implemented context management.Though /goal is a step forward in long-horizon coding, it lacks task decomposition and proper handling of context - it uses a multi-tier approach that includes persistent context chaining (PCC) to memory, local vector embeddings for RAG, sliding windows, and compaction.In principle, giving codex a directive of `/goal work towards closing my open issues on github` should work but this specific execution model hits a fatal wall - Even with massive context windows and RAG, llm reasoning quality degrades significantly beyond 100-150k~ tokens, the agent continues working with wor
